Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hy...

Full description

Saved in:
Bibliographic Details
Published in:Environmental and ecological statistics 2011-03, Vol.18 (1), p.93-108
Main Authors: Falk, Matthew G, Denham, Robert J, Mengersen, Kerrie L
Format: Article
Language:English
Subjects:
Accuracy
Biomedical and Life Sciences
Case studies
Chemistry and Earth Sciences
Computer Science
data collection
Datasets
Ecology
Geostatistics
Health Sciences
kriging
Life Sciences
Mapping
Math. Appl. in Environmental Science
Medicine
Methods
Physics
Regression analysis
sampling
Sampling techniques
spatial data
Statistics for Engineering
Statistics for Life Sciences
Studies
Theoretical Ecology/Statistics
Topography
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63
cites cdi_FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63
container_end_page 108
container_issue 1
container_start_page 93
container_title Environmental and ecological statistics
container_volume 18
creator Falk, Matthew G
Denham, Robert J
Mengersen, Kerrie L
description This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.
doi_str_mv 10.1007/s10651-009-0122-3
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_854115672</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2279085551</sourcerecordid><originalsourceid>FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWKs_wJOL9-hMssluj1L8goKHtueQzSZLyn6ZbEH_vSkrePOQyTvhfWbIS8gtwgMCFI8RQQqkACsKyBjlZ2SBouCUp6fzpLlgtBQgLslVjAcAyJGJBdltRz153bbfWZxCks7bOou6G1vfN9kxnqo-fvnW6_Cd-d4NoUu2oc-Syho7xCm1cfJGt1mnxzEB1-TC6Tbam997SfYvz7v1G918vL6vnzbU8JJN1KIxDBxWxq3qWiArJTpumNBVZbFioK1Bl1srtQFXCKNBlrksbJnXrNSSL8n9PHcMw-fRxkkdhmPo00pVihxRyIIlE84mE4YYg3VqDL5Ln1EI6pSdmrNTKSh1yk7xxLCZicnbNzb8Df4Pupshpwelm-Cj2m8ZYA7psEJy_gPnlnzy</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>854115672</pqid></control><display><type>article</type><title>Spatially stratified sampling using auxiliary information for geostatistical mapping</title><source>ABI/INFORM Global</source><source>Springer Nature</source><creator>Falk, Matthew G ; Denham, Robert J ; Mengersen, Kerrie L</creator><creatorcontrib>Falk, Matthew G ; Denham, Robert J ; Mengersen, Kerrie L</creatorcontrib><description>This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.</description><identifier>ISSN: 1352-8505</identifier><identifier>EISSN: 1573-3009</identifier><identifier>DOI: 10.1007/s10651-009-0122-3</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Accuracy ; Biomedical and Life Sciences ; Case studies ; Chemistry and Earth Sciences ; Computer Science ; data collection ; Datasets ; Ecology ; Geostatistics ; Health Sciences ; kriging ; Life Sciences ; Mapping ; Math. Appl. in Environmental Science ; Medicine ; Methods ; Physics ; Regression analysis ; sampling ; Sampling techniques ; spatial data ; Statistics for Engineering ; Statistics for Life Sciences ; Studies ; Theoretical Ecology/Statistics ; Topography ; Variables</subject><ispartof>Environmental and ecological statistics, 2011-03, Vol.18 (1), p.93-108</ispartof><rights>Springer Science+Business Media, LLC 2009</rights><rights>Springer Science+Business Media, LLC 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63</citedby><cites>FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/854115672/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/854115672?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,11667,27901,27902,36037,44339,74638</link.rule.ids></links><search><creatorcontrib>Falk, Matthew G</creatorcontrib><creatorcontrib>Denham, Robert J</creatorcontrib><creatorcontrib>Mengersen, Kerrie L</creatorcontrib><title>Spatially stratified sampling using auxiliary information for geostatistical mapping</title><title>Environmental and ecological statistics</title><addtitle>Environ Ecol Stat</addtitle><description>This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.</description><subject>Accuracy</subject><subject>Biomedical and Life Sciences</subject><subject>Case studies</subject><subject>Chemistry and Earth Sciences</subject><subject>Computer Science</subject><subject>data collection</subject><subject>Datasets</subject><subject>Ecology</subject><subject>Geostatistics</subject><subject>Health Sciences</subject><subject>kriging</subject><subject>Life Sciences</subject><subject>Mapping</subject><subject>Math. Appl. in Environmental Science</subject><subject>Medicine</subject><subject>Methods</subject><subject>Physics</subject><subject>Regression analysis</subject><subject>sampling</subject><subject>Sampling techniques</subject><subject>spatial data</subject><subject>Statistics for Engineering</subject><subject>Statistics for Life Sciences</subject><subject>Studies</subject><subject>Theoretical Ecology/Statistics</subject><subject>Topography</subject><subject>Variables</subject><issn>1352-8505</issn><issn>1573-3009</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNp9kE1LAzEQhoMoWKs_wJOL9-hMssluj1L8goKHtueQzSZLyn6ZbEH_vSkrePOQyTvhfWbIS8gtwgMCFI8RQQqkACsKyBjlZ2SBouCUp6fzpLlgtBQgLslVjAcAyJGJBdltRz153bbfWZxCks7bOou6G1vfN9kxnqo-fvnW6_Cd-d4NoUu2oc-Syho7xCm1cfJGt1mnxzEB1-TC6Tbam997SfYvz7v1G918vL6vnzbU8JJN1KIxDBxWxq3qWiArJTpumNBVZbFioK1Bl1srtQFXCKNBlrksbJnXrNSSL8n9PHcMw-fRxkkdhmPo00pVihxRyIIlE84mE4YYg3VqDL5Ln1EI6pSdmrNTKSh1yk7xxLCZicnbNzb8Df4Pupshpwelm-Cj2m8ZYA7psEJy_gPnlnzy</recordid><startdate>20110301</startdate><enddate>20110301</enddate><creator>Falk, Matthew G</creator><creator>Denham, Robert J</creator><creator>Mengersen, Kerrie L</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7ST</scope><scope>7UA</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>H97</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L.G</scope><scope>LK8</scope><scope>M0C</scope><scope>M0N</scope><scope>M2P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>RC3</scope><scope>SOI</scope></search><sort><creationdate>20110301</creationdate><title>Spatially stratified sampling using auxiliary information for geostatistical mapping</title><author>Falk, Matthew G ; Denham, Robert J ; Mengersen, Kerrie L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Accuracy</topic><topic>Biomedical and Life Sciences</topic><topic>Case studies</topic><topic>Chemistry and Earth Sciences</topic><topic>Computer Science</topic><topic>data collection</topic><topic>Datasets</topic><topic>Ecology</topic><topic>Geostatistics</topic><topic>Health Sciences</topic><topic>kriging</topic><topic>Life Sciences</topic><topic>Mapping</topic><topic>Math. Appl. in Environmental Science</topic><topic>Medicine</topic><topic>Methods</topic><topic>Physics</topic><topic>Regression analysis</topic><topic>sampling</topic><topic>Sampling techniques</topic><topic>spatial data</topic><topic>Statistics for Engineering</topic><topic>Statistics for Life Sciences</topic><topic>Studies</topic><topic>Theoretical Ecology/Statistics</topic><topic>Topography</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Falk, Matthew G</creatorcontrib><creatorcontrib>Denham, Robert J</creatorcontrib><creatorcontrib>Mengersen, Kerrie L</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 3: Aquatic Pollution &amp; Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Biological Sciences</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Environmental and ecological statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Falk, Matthew G</au><au>Denham, Robert J</au><au>Mengersen, Kerrie L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatially stratified sampling using auxiliary information for geostatistical mapping</atitle><jtitle>Environmental and ecological statistics</jtitle><stitle>Environ Ecol Stat</stitle><date>2011-03-01</date><risdate>2011</risdate><volume>18</volume><issue>1</issue><spage>93</spage><epage>108</epage><pages>93-108</pages><issn>1352-8505</issn><eissn>1573-3009</eissn><abstract>This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s10651-009-0122-3</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1352-8505
ispartof Environmental and ecological statistics, 2011-03, Vol.18 (1), p.93-108
issn 1352-8505
1573-3009
language eng
recordid cdi_proquest_journals_854115672
source ABI/INFORM Global; Springer Nature
subjects Accuracy
Biomedical and Life Sciences
Case studies
Chemistry and Earth Sciences
Computer Science
data collection
Datasets
Ecology
Geostatistics
Health Sciences
kriging
Life Sciences
Mapping
Math. Appl. in Environmental Science
Medicine
Methods
Physics
Regression analysis
sampling
Sampling techniques
spatial data
Statistics for Engineering
Statistics for Life Sciences
Studies
Theoretical Ecology/Statistics
Topography
Variables
title Spatially stratified sampling using auxiliary information for geostatistical mapping
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T23%3A49%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatially%20stratified%20sampling%20using%20auxiliary%20information%20for%20geostatistical%20mapping&rft.jtitle=Environmental%20and%20ecological%20statistics&rft.au=Falk,%20Matthew%20G&rft.date=2011-03-01&rft.volume=18&rft.issue=1&rft.spage=93&rft.epage=108&rft.pages=93-108&rft.issn=1352-8505&rft.eissn=1573-3009&rft_id=info:doi/10.1007/s10651-009-0122-3&rft_dat=%3Cproquest_cross%3E2279085551%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c382t-e1cc20f1bcf9dd512861f3c25abbe1b20aec1f4ee6ac0f75ca068467e84d28a63%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=854115672&rft_id=info:pmid/&rfr_iscdi=true